SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1926–1950 of 3874 papers

TitleStatusHype
Deep Super-Resolution Network for Single Image Super-Resolution with Realistic Degradations—0
Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound—0
Deep unfolding Network for Hyperspectral Image Super-Resolution with Automatic Exposure Correction—0
Deep Unrolled Network for Video Super-Resolution—0
Deformable-Detection Transformer for Microbubble Localization in Ultrasound Localization Microscopy—0
Deformable Kernel Convolutional Network for Video Extreme Super-Resolution—0
Deform-Mamba Network for MRI Super-Resolution—0
Degenerative Adversarial NeuroImage Nets for Brain Scan Simulations: Application in Ageing and Dementia—0
Degradation-Guided Meta-Restoration Network for Blind Super-Resolution—0
Degrees of freedom for off-the-grid sparse estimation—0
Del-Net: A Single-Stage Network for Mobile Camera ISP—0
DELTAR: Depth Estimation from a Light-weight ToF Sensor and RGB Image—0
Delta-WKV: A Novel Meta-in-Context Learner for MRI Super-Resolution—0
DEM Super-Resolution with EfficientNetV2—0
Denoising Diffusion Probabilistic Models for Robust Image Super-Resolution in the Wild—0
Dense Dual-Attention Network for Light Field Image Super-Resolution—0
Densely Connected High Order Residual Network for Single Frame Image Super Resolution—0
Dense U-net for super-resolution with shuffle pooling layer—0
Depth Anything with Any Prior—0
Depth Separable architecture for Sentinel-5P Super-Resolution—0
Depth Super Resolution by Rigid Body Self-Similarity in 3D—0
Depth Super-Resolution from Explicit and Implicit High-Frequency Features—0
DepthwiseGANs: Fast Training Generative Adversarial Networks for Realistic Image Synthesis—0
Designing A Composite Dictionary Adaptively From Joint Examples—0
Detailed 3D Human Body Reconstruction from Multi-view Images Combining Voxel Super-Resolution and Learned Implicit Representation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified